零编程打造个性化AI聊天机器人

Table of Contents

1. Introduction
2. Setting up the Chatbot
3. Creating a Chat GPT Workspace
4. Integrating Open AI API
5. Creating a Chat GPT Demo
6. Building the Chatbot Flow
7. Adding the Typing Effect
8. Improving the Chatbot Flow
9. Continuing the Conversation with Chat GPT
10. Limitations and Solutions
11. Conclusion

Introduction

In this tutorial, we will learn how to build a chatbot using the Chat GPD API. The chatbot will be built within our platform, so You don't need any recording skills or a complex setup. We will guide you through the process of setting up the chatbot, integrating the Open AI API, creating a Chat GPT workspace, and building the chatbot flow. We will also cover how to add a typing effect, improve the chatbot flow, and Continue the conversation with Chat GPT. Finally, we will discuss the limitations of the platform and provide solutions. So let's get started!

Setting up the Chatbot

To begin, you need to sign up for our platform, where you will have a 14-day free trial to try out our features. Once you have set up your account, Create a new workspace for your chatbot. In the workspace, you will find options to integrate various channels like Messenger or Instagram. For the purposes of this tutorial, we will focus on building a web chatbot.

Creating a Chat GPT Workspace

In the workspace, go to the integration section and select Open AI integration. You will need to provide your API key, which you can generate from your Open AI account. After saving the API key, verify that the integration is successful. With the integration complete, you can now create a chatbot.

Integrating Open AI API

Go to the Omni Channel and select the option to set up a web chatbot. Give your chatbot a name and choose the blank template. This will create a new bot where you can build the chatbot flow. You will use the Flow Builder, which provides a visual interface for creating the chatbot.

Building the Chatbot Flow

In the Flow Builder, start by adding a question block to Collect input from the user. Use a text block to prompt the user with a question like, "How may I help you?" Save the user's response in a variable, which we will call the question variable.

Next, add an action block to send the user's question to the integration. Select the Open AI integration and choose the chat GPT copy. Leave the model as GPT 3.5, and map the question variable to the message input. Set the maximum tokens to 500 to ensure a decent response length.

Adding the Typing Effect

To make the chatbot experience more interactive, we can add a typing effect. This effect gives the appearance that the chatbot is typing or waiting for a response. However, please note that this effect is only supported on web, Messenger, and Telegram. It is not supported on platforms like WhatsApp or Instagram.

To add the typing effect, insert a delay of one Second before the Open AI response. This will create a pause between the user's question and the chatbot's response, making it seem like the chatbot is typing. This small Detail adds a more human-like touch to the conversation.

Improving the Chatbot Flow

At this stage, you have built a basic chatbot using the Chat GPT API. However, we can further improve the flow to make it more dynamic. For example, after the chatbot responds, we can loop back to the initial question block. This allows the chatbot to respond to multiple user queries in a single conversation.

To loop the conversation back, add a loop path from the Open AI response block to the question block. This will ensure that the conversation continues seamlessly, and the chatbot can respond to new questions without starting a new conversation.

Continuing the Conversation with Chat GPT

In the previous example, the chatbot responded to user queries but did not remember the previous conversation. However, Chat GPT has the ability to remember the conversation history and continue the dialogue. To enable this feature, we need to store the entire conversation in a JSON variable.

To do this, create a user field called "Chat GPT History" and set its Type as JSON. Insert a JSON operation block before the integration block to insert the user's response into the JSON variable. Then, map the JSON variable to the messages input in the integration block. This will ensure that the entire conversation is stored and used for generating responses.

Limitations and Solutions

While using the JSON variable for conversation history provides continuity, there is a limitation to consider. The platform currently has a restriction on the size of the JSON variable, which can only store up to 5000 characters. If the conversation exceeds this limit, you won't be able to store any further data. To overcome this limitation, you can use the JSON operation block's "Slice the Item" feature to keep only the last few items of the conversation.

Conclusion

In this tutorial, you have learned how to build a chatbot using the Chat GPD API within our platform. You have learned how to set up the chatbot, integrate the Open AI API, create a chatbot flow, add a typing effect, and continue the conversation using the chat history. You have also been provided with a solution for handling the limitations of the JSON variable. Now, it's your turn to explore and customize the chatbot to suit your needs. Have fun experimenting!

Highlights

• Learn how to build a chatbot using the Chat GPD API
• Set up the chatbot within our platform with a 14-day free trial
• Integrate the Open AI API to enhance the chatbot's capabilities
• Build a chatbot flow using the Flow Builder
• Add a typing effect to make the conversation more interactive
• Loop the conversation back to continue responding to user queries
• Store the entire conversation history using a JSON variable
• Overcome the limitation of the JSON variable's size
• Customize and deploy your chatbot across various platforms
• Enjoy experimenting and creating your unique chatbot experience

FAQ

Q: Can I build a chatbot without coding skills? A: Yes, with our platform and the Chat GPD API, you can build a chatbot without any coding skills. The visual interface and pre-built blocks make it easy to create a functional chatbot.

Q: Can I integrate the chatbot with other social media channels? A: Yes, once your chatbot is ready, you can connect it with various social media channels like Messenger, Instagram, Telegram, and more. This allows you to reach a wider audience and engage with users on their preferred platforms.

Q: What are the advantages of using the Chat GPD API? A: The Chat GPD API provides a cost-effective solution for building chatbots. It is 10 times cheaper than other API models, making it suitable for various use cases. It also offers customization options and generates responses based on the user's inputs.

Q: Is there a character limit for the conversation history? A: Yes, currently, the platform has a limit of 5000 characters for the JSON variable used to store the conversation history. If the conversation exceeds this limit, you can use the JSON operation block's "Slice the Item" feature to keep only the most recent conversations.

Q: Can I deploy the chatbot on WhatsApp? A: Unfortunately, the typing effect feature is not supported on WhatsApp or Instagram. However, you can deploy the chatbot on web, Messenger, and Telegram to utilize this interactive feature.

Q: How can I handle conversation continuity in the chatbot flow? A: By storing the entire conversation history in a JSON variable, you can enable the chatbot to remember previous interactions and provide a seamless conversation experience. Looping the conversation back to the initial question block allows the chatbot to respond to new questions without starting a new conversation.